Dear all,
this week the MOOC "Autonomous Navigation for Flying Robots" starts on EdX.
The course aims at graduate students in robotics and computer vision. The
course consists of approximately 45-60 minutes video per week and weekly
exercises. To maximize the learning effect, we developed a web-based
quadrotor simulator that can be programmed by the students in Python.
Teaser video:
http://www.youtube.com/watch?v=XkVFLyeaIIo
To sign up for the course, please follow this link:
https://www.edx.org/course/tumx/tumx-autonavx-autonomous-navigation-1658
Best regards
Jürgen Sturm
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In this course, we will introduce the basic concepts for autonomous
navigation with quadrotors, including topics such as probabilistic state
estimation, linear control, and path planning.
In recent years, flying robots such as miniature helicopters or quadrotors
have received a large gain in popularity. Potential applications range from
aerial filming over remote visual inspection to automatic 3D reconstruction
of buildings. Navigating a quadrotor manually requires a skilled pilot and
constant concentration. Therefore, there is a strong scientific interest to
develop solutions that enable quadrotors to fly autonomously and without
constant human supervision. This is a challenging research problem because
the payload of a quadrotor is uttermost constrained and so both the quality
of the onboard sensors and the available computing power is strongly
limited.
In this course, we will introduce the basic concepts for autonomous
navigation for quadrotors including topics such as probabilistic state
estimation, linear control, and path planning. You will learn how to infer
the position of the quadrotor from its sensor readings, how to navigate
along a series of waypoints, and how to plan collision free trajectories.
The course consists of a series of weekly lecture videos that we be
interleaved by interactive quizzes and hands-on programming tasks. The
programming exercises will require you to write small code snippets in
Python to make a quadrotor fly in simulation.
This course is intended for graduate students in computer science,
electrical engineering or mechanical engineering. The course is based on
the TUM lecture “Visual Navigation for Flying Robots” which received the
TUM TeachInf best lecture award in 2012 and 2013. The course website from
last year (including lecture videos and course syllabus) can be found here:
http://vision.in.tum.de/teaching/ss2013/visnav2013